Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/159357
Title: Unconstrained tracking MPC for continuous-time nonlinear systems
Authors: Long, Yushen
Xie, Lihua
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Long, Y. & Xie, L. (2021). Unconstrained tracking MPC for continuous-time nonlinear systems. Automatica, 129, 109680-. https://dx.doi.org/10.1016/j.automatica.2021.109680
Project: ACCL200013
Journal: Automatica
Abstract: In this paper, we extend unconstrained model predictive control (MPC) from setpoint stabilization to dynamic reference tracking for continuous-time nonlinear systems. In particular, we focus on the case when the reference cannot be perfectly tracked by the system due to dynamics and/or constraints. Under the incremental stabilizability assumption and an additional dissipativity assumption, the practical stability of tracking the unknown optimal reachable reference trajectory is proved even though the controller does not know such a reference explicitly.
URI: https://hdl.handle.net/10356/159357
ISSN: 0005-1098
DOI: 10.1016/j.automatica.2021.109680
Rights: © 2021 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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